Research Agenda

Research agendas across diverse scientific fields are currently focusing on improving the efficiency and trustworthiness of research processes and outputs. Key areas of investigation include mitigating biases in AI models, particularly in areas like sign language recognition and fairness in machine learning pipelines, and enhancing the explainability and usability of generative AI. This involves developing novel algorithms and architectures, such as hierarchical transformers and graph neural networks, to improve model performance and address challenges like data dependency and the need for more effective human-AI collaboration in research. Ultimately, these efforts aim to accelerate scientific discovery, improve the reliability of research findings, and foster more equitable and impactful applications of AI.